America's dependence on reliable electric power, and our individual and collective vulnerability<br>to power disruption, continues to grow. While it would be technically possible to make changes<br>that could sustain many critical electricity-dependent services during widespread and longlasting<br>outages by implementing smart grid technologies, distributed generation resources, and<br>other technologies, these technologies would require incremental investments where the benefits<br>are uncertain and difficult to quantify in many cases.<br>For many years, distribution utilities in United States have conducted studies of the value that<br>customers place on reliable electric services. However, these studies and associated literature<br>suffer from several shortcomings: they have not devoted much effort to help respondents fully<br>understand and consider the various implications of hypothetical outages that respondents may<br>not have experienced nor previously considered; they have done little to minimize cognitive<br>biases; they have focused almost exclusively on brief outages that last only up to a few hours;<br>and, they have only considered the difference between full backup service and no service. Hence,<br>their results are not adequate to assess how much individuals or society might, or should, be<br>willing to avoid longer outages or provide full or limited backup service in the event of large<br>outages of long duration.<br>To address these issues, we have developed and demonstrated a set of improved methods that<br>help residential customers think systematically about the value they attach to reliable electric<br>service and have used the elicited informed judgments to illustrate how the results could be used<br>for local or regional-decision-making.<br>After introducing the issues in Chapter 1, Chapter 2 summarizes a new elicitation framework that<br>has been designed to help residential electricity customers think carefully about the value they attach to reliable electric service. The survey framework was applied to a convenience sample of<br>residents in Allegheny County, Pennsylvania to assess their willingness-to-pay to receive backup<br>services during a hypothetical 24-hour outage on a hot summer day. The face-to-face interview<br>results suggest that there exists a considerable amount of consumer surplus associated with<br>providing partial electric backup service (i.e., the respondents’ willingness-to-pay per kWh is<br>significantly higher for their first bit of electricity than the value of the last amount consumed).<br>Further, the assessed value of sustaining demands the respondents assessed to be high priority<br>significantly increased as they receive additional information and better understood the outage<br>scenario and its consequences.<br>In Chapter 3, we estimated the cost to implement to implement the capability to provide limited<br>emergency backup power service using isolated distribution feeders, evenly distributed the<br>incremental investment costs across to all residential customers across outages, compared the<br>required service payment with the measured willingness-to-pay distribution, and explored<br>whether and when such investments can be justified. We first conducted a series of order of<br>magnitude calculations and found that providing the low-amperage backup service can be more<br>cost-effective than buying a small portable generator and storing diesel or gasoline for refueling<br>even if a 24-long outage occurs once every 20 years, and the backup service appears to be more<br>cost-effective if a region is expected to suffer more frequent and longer outages. In addition to<br>the assessments using private willingness-to-pay, the chapter also considers two methods that<br>might be used to recover system upgrade costs without raising a serious equity issue nor<br>imposing an excessive burden to either residential customers or the region.<br>In order to explore respondents’ willingness-to-pay under a variety of scenarios for different<br>geographical regions more efficiently, the face-to-face survey framework has been modified for online use. Chapter 4 first describes the details of the generalizable web-based survey framework<br>that a researcher or decision-maker can use to design ones’ own outage scenarios. It also<br>addresses several factors that are assumed to influence estimates from stated preference valuation<br>studies. The framework was then used to elicit the economic and social preferences for reliable<br>electric backup services during hypothetical 10-day widespread outages from a sample of<br>residents of the Northeastern United States. We first demonstrated the importance of helping<br>respondents fully consider the various aspects of the consequences of the hypothetical outages<br>and better articulate their values, and then used the elicited preferences to explore whether and<br>how much some of the factors that are known to affect respondents’ risk perceptions influence<br>their willingness-to-pay values for reliable electric services during the hypothetical outages. The<br>chapter concludes with a discussion of why exploring preferences for reliable electric services<br>under a variety of scenarios and constructing customer damage functions for electricity<br>customers are important, and what we see as future behavioral research needs.<br>Finally, in Chapter 5, we discussed how the elicited preferences can be used to make more<br>informed and collective societal decisions. Benefit-cost analysis and other forms of analysis have<br>been widely used in policy analysis and government decision-making. However, only<br>uncertainties about costs and physical states of the world are considered, neglecting uncertainty<br>about the level of benefits that come from the value the public places on policy outcomes. In this<br>chapter, we proposed such an approach that incorporates uncertainties in individual preferences.<br>Using the public valuations of implementing smart grid technologies to mitigate impacts of<br>large-regional outages, we showed uncertainty in individual preferences, when aggregated to<br>form societal preference intervals, can substantially change the decision society would make. <br>